Slope One, non-trivial item-based and Rating-Based CF Algorithm

Reading time ~17 minutes

  • References
  • Previous Solution
    • using linear regression f(x) = ax+b, leading to severe overfitting
  • Alternative Solution
    • learn a simpler predictor (called slope one) , f(x) = x+b
  • Examples
  • Features
    • subtract the rating of the two items
    • For each user, predict the <item, rating> pairs of those items this user has not rated.
    • predict another user’s rating of those items
    • support both online queries and dynamic updates
    • reduces storage requirements and latency
    • scalable with respect to the number of users
    • deprecated in Mahout 0.8
  • Drawback
    • Predicted ratings of some items sometimes are larger than 5. (Need to figure out what’s wrong here.)
  • Datasets
  • Source Code
  • Practice

OpenCV haar training to .xml file

one of the object detection methods in computer vision Continue reading